[Updated 2023-11-12 for farming experience and PoE splitter] [Updated 2023-11-22 for Pi 5 4GB plot time and case experience]
I was on the waitlist for Raspberry Pi 5 8GB at my local computer shop, Central Computer. I had to go in to get a cooler for a new machine I am going to be building this month, and at the checkout I asked if they had any Pi 5 boards left, thinking I’d play with a 4GB board if they had any left.
“We’ve got 4GB and 8GB, which would you like?”
Well, of course, 8GB.
I already had a couple of cases coming from Amazon in preparation, and a 5V4A PSU (the 5V5A one for full power with the new Pi is already hard to come by), and a fresh MicroSD card from my last visit to Central, so I was ready to go.
I was planning to wait a while at first, but someone on one of the Chia Discords asked about Pi5 for Chia, I took the challenge on.
I’ve started work on a walkthrough of Chia farming from download to payout. It’s turned out to be a bit more challenging than I thought, but I’m still plowing through.
This video (below) is NOT the walkthrough. It is a quick overview, with an hour of sped-up node syncing. Three hours to get the last four weeks synced… not very fun but it makes a point, and gets some content up on the Andromedary Instinct YouTube channel.
Why does this matter? Well, syncing the blockchain to your node is necessary to plot and do transactions (there may be workarounds for both, but the usual path is to sync a full node and then start farming). That’s a pretty slow process.
On a very well-tuned farmer with great network and I/O, I suspect you can get a node synced in a day or so. Last time I synced from scratch on a Raspberry Pi, I believe it was 11 days, and would be longer today. The machine in this video took three hours to sync 4 weeks of activity, and that skips over the dust storm phase of the blockchain (which effectively knocked a lot of slower nodes offline until Chia Network did some software enhancements to better deal with dust storms).
By using BitTorrent to grab a snapshot (about 65GB compressed, 125GB uncompressed) in a few hours, you skip closer to the front of the line in syncing status. You can then “resume” syncing from the start of July and even on a suboptimal machine like my test machine, you’ll be done in under a day.
This video also shares one of the better guides to moving your database directory. In my case, the boot drive it was originally syncing to is a 256GB drive, and it would eventually fill up the drive. I moved it off to a second SSD so that the boot drive won’t degrade.
Building that system, and what I’d do differently
I realized as I started plotting (heh) the video flow that it would be easier to start with a fresh computer. I had another use for an Alder Lake-based machine coming up, and I managed to get a complete system new in open box for $250 locally, so I went for it. As configured, it cost me less than $500, but if I were building it for long term Chia use without “free” review stock from Amazon Vine, I’d make a few other changes.
Bill of Materials, as built ($537 with caveats)
HP Pavilion TP01-3016, i5-12400, 12gb RAM – $250 on Facebook Marketplace with smaller NVMe boot drive
This HP desktop system maxes at 32GB RAM, so plotting may be limited even with a GPU. However, for storage it’s pretty good, with two 5GBit USB-A ports, two 10GBit USB-A ports, and one 10GBit USB-C port on the front (in addition to two USB 2.0 ports on the back). The board supports two SATA drives with power connectors plus the NVMe. And it’s not a bad CPU – 6 P-Cores with hyperthreading.
Once I finish the video, I’ll be swapping out the boot drive for a better one to install Ubuntu and Arweave on. I still prefer running my node databases on moderate to good performance NVMe over an economy SATA drive whenever possible.
Some other options for plotting and farming systems
This HP desktop build met my primary criterion – ability to get a system cheap and quick and local to set up Chia from the ground up. But as noted above, it’s not perfect, and has definite limits (like one x1 and one x16 PCIe slot, only two SATA drives, 32GB max RAM).
I have two T7910s, and even though they’re several years old, they have a lot of expandability and performance while being fairly manageable in size, shape, noise level, and power draw.
This one has two E5-2695v4 processors and 512GB RAM included. You can branch out into compressed plots and/or RAM-based plotting, both of which will accelerate your plotting. With several x16 PCIe slots and either 4 3.5″ or 8 2.5″ drives (not sure which is the case on this system), you can expand with GPUs, storage adapters, internal SAS/SATA drives, or even faster networking.
My primary plotter is still a T7910 with two E5-2650Lv4 (14c28t) processors and 128GB RAM, plus a RTX3060 GPU
If you’re looking for a slightly different config, there are a number of options with different mix of CPU, RAM, and storage at the Amazon Renewed store.
Another alternative is to go a bit more modern with a T7920, which uses first gen Xeon Scalable processor instead of the Xeon E5 v4 line. There are a fair number of first gen Xeon Scalable gold processors for double digit prices on eBay in case you start with a silver or bronze level processor.
Mini PCs, primarily for farming or uncompressed plotting
There are a lot of NUCs and NUC-Class systems out there. I’ve got systems from ACEMAGICIAN, GEEKOM, and Beelink in the home lab/studio, as well as my classic Chia NUC plotter, the NUC10i7FNH from a couple of years ago.
These are not very expandable in terms of interfaces or GPUs, but with Thunderbolt you could use a Thunderbolt Hub to attach additional USB hubs and drives, or a Thunderbolt PCIe enclosure to attach a SAS card or GPU.
At some point, however, if you’re looking at expanding your NUC or mini-PC that much, though, you may want to consider either a NAS or a desktop/workstation/server with SAS enclosures to handle the drives.
A lot of people hate reading documentation, so I’m writing meta-documentation based on the documentation to help you get things going with FlexFarmer and Gigahorse compressed plots.
The authoritative site for Gigahorse details is madMAx43v34’s github, which is where you can find all of his software. And any references in this post will be to Gigahorse software, not Bladebit.
And as always, anything I post even vaguely related to Flexpool here on rsts11.com is not official or endorsed by Flexpool, even though I have been on their support team for over two years now.
In this post:
Farming Gigahorse compressed plots on Windows
Using a remote GPU for farming from Windows or Linux
Selecting which GPUs to use for farming
There is no spoon
A shortcut to farming compressed plots (albeit Bladebit compressed), at a premium
Farming Gigahorse compressed plots on Windows (kinda)
You need a Linux system to farm compressed plots at this point. Luckily if you have Windows 10 or later with current patches, you have a Linux system ready to install.
I’ve co-written a guide to FlexFarmer + Gigahorse compressed plots + Windows + WSL over on Reddit. It’s not an official supported deployment for Flexpool (i.e. the pool doesn’t provide official support for it) but it does work. I’ve used it myself on a small farm to verify the guide, and many others do the same with as much as a petabyte or more.
Using a remote GPU for farming from Windows or Linux
But maybe your Windows machine doesn’t have a suitable GPU, or you want to farm using an AMD GPU when the Gigahorse module in FlexFarmer only recognizes NVIDIA.
That’s easier to document, and in fact it works with Linux farmers too (I set up remote compute from my Linux plotter to my Windows 10 desktop so I could dedicate the GPU to plotting for a while).
On the machine with the GPU you want to share (the “recompute server”), either get the Gigahorse bundle for the relevant OS, or download the chia_recompute_server program from the appropriate directory.
On the recompute server, make the downloaded binary executable (on Linux), and then run it.
That’s it.
Now on your farmer, you need to set the environment variable CHIAPOS_RECOMPUTE_HOST to your recompute server’s name or IP address.
Note that this name does NOT mean you need to be running chiapos plotter or the Chia or Gigahorse full node. If you are running Gigahorse farmer, you have to restart the Gigahorse farmer after setting the variable, but for FlexFarmer you do not.
For example, if your recompute server is 192.168.0.2, you enter:
If you have multiple GPUs but you want to only use selected GPUs with FlexFarmer, Max’s documentation explains how to do this. It’s worth noting that this generally applies to any CUDA software.
Use the “nvidia-smi” command inside of WSL, or under Linux natively, to list your GPUs and determine which device numbers apply.
You use the CUDA_VISIBLE_DEVICES environment variable to choose the devices you want the farmer to use. In the example above, I only have one GPU so it’s device 0, but if you have multiples, they will be listed and you can choose the ones you want.
From Max’s documentation:
Once again, the note above about full notes applies. If you’re using a configured FlexFarmer instance, just set this environment variable and the CUDA libraries used in the Gigahorse module will pick it up.
If you want to disable GPU usage in FlexFarmer, there’s a two line configuration option to disable hardware (GPU) acceleration.
Using Evergreen Miner as a shortcut to compressed farming
This is a somewhat controversial option, and if you already have the hardware to plot and farm and can manage your software on your own, you don’t need Evergreen.
However, if you want a power optimized option where you don’t have to have a plotter at all, and just buy drives in enclosures with plots already made for you, Evergreen Miner is a viable option.
In short, you buy an “Evergreen Hub” which is a single-board computer with a customized Linux install that provides all the software for farming, interacting with the mobile app, and managing storage attached to it. Then you buy (or provide and plot your own) hard drives that connect to the Hub over USB.
Generally you’d buy a starter kit that includes 1 or more hard drives pre-loaded with plotted drives. You can then add more drives, up to 25 per hub, either through their pre-plotted offer or sourced and plotted by you (if you choose to expand on your own).
With the kits and drives from Evergreen, you get the needed cabling, including a single PSU (12V 10A) and splitter cables, as well as everything to connect the hub to the drives and to your network.
Even though I’ve been plotting since mainnet launch in 2021, and have plenty of gear and ~160TB plotted and farming, I bought a 12TB starter kit and it’s been chugging along.
I believe the beta compressed-plot farmer for Evergreen is going into general release in the next week or two (i.e. mid August 2023), and the Chia Blockchain software release that includes Bladebit compressed plot generation is coming soon after (it’s in release candidate 3 as I write this). When those both happen, I’ll be giving a try to the Bladebit compression, and may get a chance to update this post with the details.
Where do we go from here?
I’m working on some video demos of the Chia process, from initial downloads to first payout. I hope those will go live later this month.
I also have some mini-PC reviews in the buffer. Stay tuned. It’s not all crypto out there after all.
Have you been working with compressed plots or Evergreen Miner or both? Any observations, discoveries, or questions? Join us in the comments below.
This isn’t entirely a Chia post, although it was inspired as such. You may have seen a teaser post on r/Chia, but if you didn’t, you’ll be okay.
In my time in the Evergreen Miner community, and elsewhere, I’ve had people ask if you can plot Chia on a Raspberry Pi.
I’m pleased to report that it can be done on a 4GB Raspberry Pi 4B, and you can create a Gigahorse compressed C5 plot in about 22.1 hours. For this test I used the 4GB board, booted from a MicroSD card, with an external USB 3.0 to SATA enclosure and a 1.92TB Dell Enterprise SATA SSD.
I wanted to try on my remaining 8GB board, but it is having issues with USB storage, so after a couple of hours of testing, I set it aside and thought about other low cost, low power options.
I tried my Zimaboard 216 single-board x86_64 server, featuring a 2 core Celeron processor, 2GB RAM, 16GB eMMC storage, a PCIe 2.0 x4 slot, two SATA ports with power (for SSDs), two ports USB 3.0, dual Gigabit Ethernet, and a completely silent (fanless) design. Alas, while the plotter “worked” on this system, 2GB was not enough, and the OOM killer process took down the plotter. I have a Zimaboard 832 (the 2021 green edition, good for Chia) but ran out of weekend so I just went with plan C.
Enter the Orange Pi
I’d heard good things from the Evergreen co-founder about the Rockchip 3588, and ordered an Orange Pi 5B with 16GB RAM and 256GB eMMC. I got it over the weekend, hooked it up, discovered that you have to use rkdevtools to install it, but still could not get video or network connectivity with it. It got power, and drove the fan, but no status LEDs, no network LEDs, and no rkdevtools access.
After checking with a friend, I learned that it should not have come loose in a cardboard box.
My first Orange Pi arrived exactly like this product page photo, but with the wifi antennas connected. No anti-static bag, no packaging protection, and no functionality.
I put in for an exchange, dropped off the board at my local Whole Foods for return, and got the replacement board Tuesday morning. This time, it was in a sealed anti-static foil bag in a plastic protective case. Much better.
The second Orange Pi arrived like this, and seems to have worked.
I set about doing the board bring-up. It’s more complicated than a Raspberry Pi, requiring the Rockchip dev tools package, a boot loader, and a specific Orange Pi build of Ubuntu. The well-formatted instructions for Klipper on the 5B from 3DP and Me were very useful for getting things going. You can also get the apparently-official 357 page users guide from Orange Pi’s Google Drive that has the instructions and more. I don’t recommend it if you can avoid it, though (ps: you probably can’t completely avoid it, but maybe don’t start with it).
The software downloads were a bit confusing for me… you have to get an Android image download (even if you’re not installing Android) from another Google Drive, which includes the RKDevTool program for Windows, the “DriverAssitant” bundle including the USB driver for board bringup, and the Miniloader folder with boot loader and configuration. It’s a long way from Raspberry Pi Imager or Rufus. And random Google Drive download sources are sketchy.
Anyway, after waiting two hours for the “download complete” message in RKDevTool that never came, I tried logging in via ssh with root / orangepi and got in. (Page 87 on the manual above, so maybe don’t completely avoid it).
From there I made a few more adjustments:
Installed Zerotier VPN and joined it to my network.
Executed ‘apt update’ followed by ‘apt upgrade’
Set my time zone away from Asia/Shanghai with ‘dpkg-reconfigure tzdata’
Verified that I could log in with orangepi, and left the root shell
Changed root and orangepi passwords
Rebooted to make the updates take effect (and to install my external USB SSD)
There are a lot of Orange Pi 5 series models
Another odd sequence of discoveries is that there are three primary models of the Orange Pi 5, each of which may come with different RAM and eMMC storage. I learned some of the distinctions after digging for my one NVMe drive that was smaller than 2280, and then finding there was no NVMe slot.
Here are the three models, with pricing for the smallest configuration I could find on Amazon. I would really recommend the 16GB models, and max out the storage if you go 5B. But it depends on your use case of course.
Orange Pi 5 models, with prices as of 7/25/2023 (affiliate links for Amazon, direct links for OrangePi.org).
Be aware that on the 5 and 5B, the USB 3.0 port shares a dual blue port assembly with a 2.0 port–the 3.0 port is on the top, and the bottom port, despite being blue, is USB 2.0. The 5 Plus has a pair of USB 2.0 (black) ports, and a pair of USB 3.0 (blue) ports.
On the Orange Pi 5 and 5B, the only USB 3.0 Type A port is the top port.
You can use a 5V/~4A USB-C power supply and cable, your own HDMI cable, and run without a case (these are slightly larger than a Raspberry Pi so you can’t reuse those cases), but I decided to drop almost $30 on an add-on starter kit. This kit from GeeekPi includes a clear case with tinted top and bottom, rubber feet for said case, USB-C power supply with inline switch, a fan, heatsinks for the DRAM and CPU, a 64GB MicroSDXC card and USB-A card reader, and a HDMI cable. (The description currently says Micro HDMI cable, but the board has native full size HDMI unlike the Pi4b).
Some machines to compare with the Orange Pi 5 family
After posting my plotting tests on Reddit r/chia, someone asked and clarified a question about the Radxa Rock and ODROID machines. I did some quick research and found some viable alternatives. If you have local supply chain or Amazon Prime limitations, these may get you going faster.
Radxa’s Rock 5 Model A and ODROID M1 are comparable to the Orange Pi 5B I tested.
For an upgrade to the Orange Pi 5B Plus style, Rock PI Model B also gives you NVMe onboard and a single 2.5 Gigabit Ethernet port (vs Orange’s dual ports) and support for a Power over Ethernet hat.
If you really want to go overboard, ODROID’s H3 supports NVMe, two DDR4 SODIMMs up to 64GB, dual 2.5 Gigabit Ethernet, two onboard SATA ports, and eMMC support..
I’ve set up an Amazon wishlist to show the systems I’m looking at. If you feel generous and want to send me something from the list, I’ll be happy to give you credit when I post the testing results. If not, it’s a checklist for me to work through.
Where do we go from here?
I tried to keep this post as chia-free as possible, as it’s relevant to a lot of other use cases. I may not have completely succeeded at that. In any event, I will have a Chia plotting post around single board and small board computers in August, and a few other things in mind.
Have I missed your favorite single board computer? Share it in the comments and I’ll add it to my list.
I got a Synology DS1821+ array about two years ago, planning to finally cascade my other Synology units and let one or two go. So far, that has not happened, but I’m getting closer.
Synology DS1821+, photo courtesy of Synology. Mine looks like this but with a bit more dust.
The back story of my DS1821+
This is the 8-bay model with a Ryzen V1500B 4-core 2.2GHz processor, support for virtual machines and containers, and a PCIe slot which I filled with a dual port Mellanox ConnectX-3 (CX312A) 10 Gigabit SFP+ card which came in under $100 on eBay. The expansion options include two eSATA ports (usually used for the overly expensive DX expansion units) and four USB 3 ports (one of which now has a 5-bay Terramaster JBOD attached).
Today I could get a 40 Gigabit card for that price. In fact, I did for another project, for about $90+tax with two Mellanox cables, just last month, but I’m not sure it would work on. It’s not too hard to find one of these 10 Gigabit cards for under $50 shipped in the US. Be sure to get the dual plate or low profile version for this Synology array.
I ran it for a while with 64GB RAM (not “supported” but it works), and then swapped that out to upgrade my XPS 15 9570 laptop, putting that machine’s 32GB back into the Synology. I had a couple of 16TB MDD white label hard drives and a 256GB LiteON SSD as a cache. I know, I know, there’s NVME cache in the bottom and you can even use it as a filesystem volume now.
Here’s where something went wrong
Sometime in the past couple of updates, the SSD cache started warning that it was missing but still accessible. I ignored it, since this system doesn’t see a lot of use and I don’t really care about the cache.
Volume expansion attempt, which failed. SSD cache warning showing here as well.
Earlier this month, I got a couple more of the MDD white label drives (actually ST16000NM001G-2KK103 according to Synology Storage Manager), I was able to expand the storage pool but not the volume.
Successful storage pool expansionThe volume expansion error. No filesystem errors were discovered.
“The system could not expand Volume 1. This may be caused by file system errors. To rescue your data, please sign in to your Synology Account to submit a technical support ticket.”
Well, as I went to the Synology website to enter a ticket, I remembered the SSD issue and wondered if that caused the problem with growing the volume.
Easier to fix than I had feared
Sure enough, removing the cache made the volume expand normally, bringing me from 93% used to 45% used. Not too bad.
Where do we go from here?
At some point in the next month or two, I plan to get three more of these 16TB drives, pull the unused 8TB and unused 256GB SSD, and get the system maxed out.
I’m a bit torn between using this array to replace my Chia farms, at least for a while, or merge my other two substantial Synology arrays onto it and then use one of them (maybe the DS1515+) as the Chia farm with the DX513 and an assortment of external USB drives. Flexfarmer on Docker makes it pretty easy to run Chia farming on a Synology with minimal maintenance.
rsts11 - Robert Novak on system administration 